I'm a Data Scientist and certified AI Engineer with 10+ years building AI systems for startups and enterprise teams.
- What I build: LLM applications like copilots, RAG systems, and multi-agent workflows
- Industries: Automotive, Manufacturing, AgriTech, and MedTech
- Focus: Production-ready AI systems that work under real-world pressure
Let's connect on LinkedIn or check out some of my work below.
- Automated Patent Trend Intelligence with multi-LLM workflow sliced diligence time by ~90% → here
- On-prem AI chatbot for 300+ employees, keeping data sovereign while cutting onboarding time by ~70% → here
- AI Agent for SQL-Based Data Retrieval and Exploratory Data Analysis → here
- Customer Care Automation with multi-Agent workflow → here
- Plant-wide ergonomics assessment time reduced from 12 months to 3 weeks with 3D pose-estimation → here
My tech stack combines modern AI with production-proven tools:
- LLMs: OpenAI, Anthropic Claude, Google Gemini, Groq, Qwen
- AI Agent Orchestration: LangChain, LangGraph, PyDanticAI
- Vector Database: PostgreSQL (pgvector), Supabase, Pinecone, Qdrant
- Monitoring & Evals: Custom observability pipelines, LangSmith, LangFuse, Arize Phoenix, GuardrailsAI
- Data/Infrastructure: Python, Docker, FastAPI, REST, MCP, GitHub Actions, Pydantic, CI/CD, Azure, Databricks
- Machine Learning: Scikit-learn, Pandas, NumPy, XGBoost, PyCaret, PyTorch/Lightning
- Specialties: Context Engineering, RAG & Vision-RAG Systems, Multi-Agent Workflows
Most deliverables live inside private repositories, client-controlled GitHub orgs or air-gapped infrastructure covered by NDAs. The public projects you see highlight OSS contributions, reproducible studies, and playgrounds where I battle-test new frameworks before hardening them for secure production rollouts.
Hire me on Upwork or book a call to discuss your project.
